Video cameras are widely used for surveillance. For example, commercial Closed-Circuit Television (CCTV) systems use video cameras to enable monitoring in areas such as banks, airports, retail stores, and traffic intersections, to name a few. Present video cameras are mostly digital cameras that generate digital output (i.e., digital images). For example, an Internet Protocol (IP) video camera connects to a network (either wired or wireless) and transmits captured digital images over the network to different devices for storage, display, or analysis. Digital technologies used by video cameras enable automatic analysis of video content. For example, video cameras are used to count people going in and coming out a building. In such a case, the video cameras are often mounted overhead at the building entrance, where the video cameras have little view occlusion and people counting, thereby, is simplified. However, such people counting systems can only detect and count the number of people going in and coming out the facility, and cannot detect people while they are inside the facility. Furthermore, these people detection systems cannot distinguish one type of people (e.g., sales clerks) from other types of people (e.g., customers) due to limited information captured by the video cameras.
Detecting and classifying people using video cameras are often indispensable in many applications such as security surveillance. Employee detection using video cameras is especially useful for workforce management and operation efficiency at many workplaces. People detection systems using video cameras generally vary in their sensing and processing techniques depending on the characteristics and constraints of the specific applications of the video cameras. Despite the abundant research and exploration by both academia and commercial industry, quick and accurate people detection in real-time using video cameras remains challenging due to, for example, the wide variety of human activities and movements, cluttered backgrounds, video camera characteristics (e.g., resolution and frame rate), and large illumination changes.
Accordingly, there is a need for a method and apparatus for accurately detecting people using video cameras deployed inside and outside facilities. In particular, there is a need for a method and apparatus for detecting people within video frames based upon multiple colors within their clothing.
Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help improve understanding of various embodiments. In addition, the description and drawings do not necessarily require the order illustrated. It will be further appreciated that certain actions and/or steps may be described or depicted in a particular order of occurrence while those skilled in the art will understand that such specificity with respect to sequence is not actually required.
Apparatus and method components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the various embodiments so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein. Thus, it will be appreciated that for simplicity and clarity of illustration, common and well-understood elements that are useful or necessary in a commercially feasible embodiment may not be depicted in order to facilitate a less obstructed view of these various embodiments.